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Small edits (#257)
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@ -53,7 +53,7 @@ next to the **FILE PATH**.
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The full dataset listing (all files included) is available in the **CONFIGURATION** section under **Dataset Content**.
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This allows you to quickly compare two dataset contents and visually see the difference.
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The dataset genealogy DAG and change-set summary table is visualized in **RESULTS > PLOTS**
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The dataset genealogy DAG and change-set summary table is visualized in **PLOTS**
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<details className="cml-expansion-panel screenshot">
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@ -80,7 +80,7 @@ View a DAG of the dataset dependencies (all previous dataset versions and their
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Once a dataset has been finalized, view its genealogy in the dataset's
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page **>** **RESULTS** **>** **PLOTS**
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page **>** **PLOTS**
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<details className="cml-expansion-panel screenshot">
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<summary className="cml-expansion-panel-summary">Dataset Genealogy</summary>
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@ -465,7 +465,11 @@ By default, it stores the local path they are saved at.
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To automatically store all created models by a specific experiment, modify the `Task.init` function as such:
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```python
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task = Task.init(project_name='examples', task_name='storing model', output_uri='s3://my_models/')
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task = Task.init(
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project_name='examples',
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task_name='storing model',
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output_uri='s3://my_models/'
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)
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```
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To automatically store all models created by any experiment at a specific location, edit the `clearml.conf` (see
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@ -563,10 +567,14 @@ This method saves configuration objects as blobs (i.e. ClearML is not aware of t
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model_config_dict = {
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'value': 13.37, 'dict': {'sub_value': 'string'}, 'list_of_ints': [1, 2, 3, 4],
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}
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model_config_dict = task.connect_configuration(name='dictionary', configuration=model_config_dict)
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model_config_dict = task.connect_configuration(
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name='dictionary', configuration=model_config_dict
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)
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# connect a configuration file
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config_file_yaml = task.connect_configuration(name="yaml file", configuration='path/to/configuration/file.yaml', )
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config_file_yaml = task.connect_configuration(
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name="yaml file", configuration='path/to/configuration/file.yaml'
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)
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```
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@ -53,7 +53,7 @@ Logger.current_logger().report_scalar(
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```
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These scalars can be visualized in plots, which appear in the ClearML web UI, in the experiment's
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page **>** **RESULTS** **>** **SCALARS**.
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page **>** **SCALARS**.
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@ -65,7 +65,7 @@ ClearML automatically logs command line options defined with `argparse`. They ap
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -52,7 +52,7 @@ Task.current_task().get_logger().report_scalar(
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)
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```
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The single scalar plot for loss appears in **RESULTS** **>** **SCALARS**.
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The single scalar plot for loss appears in **SCALARS**.
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@ -75,6 +75,6 @@ All the hyperparameters appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS**.
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## Console
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Output to the console, including the text messages printed from the main Task object and each subprocess appear in **RESULTS** **>** **CONSOLE**.
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Output to the console, including the text messages printed from the main Task object and each subprocess appear in **CONSOLE**.
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@ -34,6 +34,6 @@ Parameter dictionaries appear in **General**.
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## Console
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Output to the console, including the text messages from the Task in each subprocess, appear in **RESULTS** **>** **CONSOLE**.
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Output to the console, including the text messages from the Task in each subprocess, appear in **CONSOLE**.
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@ -13,7 +13,7 @@ the autokeras [TextClassifier](https://autokeras.com/text_classifier/) class, an
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## Scalars
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The loss and accuracy metric scalar plots appear in **RESULTS** **>** **SCALARS**, along with the resource utilization plots,
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The loss and accuracy metric scalar plots appear in **SCALARS**, along with the resource utilization plots,
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which are titled **:monitor: machine**.
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@ -26,7 +26,7 @@ ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATIO
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -13,7 +13,7 @@ The example script does the following:
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## Scalars
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ClearML automatically captures scalars logged by CatBoost. These scalars can be visualized in plots, which appear in the
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[ClearML web UI](../../../webapp/webapp_overview.md), in the experiment's page **> RESULTS > SCALARS**.
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[ClearML web UI](../../../webapp/webapp_overview.md), in the experiment's page **> SCALARS**.
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@ -24,7 +24,7 @@ PARAMETERS > Args**.
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS > CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -16,18 +16,18 @@ The example code does the following:
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## Scalars
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ClearML automatically logs the histogram output to TensorBoard. They appear in **RESULTS** **>** **PLOTS**.
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ClearML automatically logs the histogram output to TensorBoard. They appear in **PLOTS**.
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## Plots
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Histograms output to TensorBoard. They appear in **RESULTS** **>** **PLOTS**.
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Histograms output to TensorBoard. They appear in **PLOTS**.
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## Logs
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -16,14 +16,14 @@ The example does the following:
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## Scalars
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The loss and accuracy metric scalar plots appear in **RESULTS** **>** **SCALARS**, along with the resource utilization plots, which are titled **:monitor: machine**.
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The loss and accuracy metric scalar plots appear in **SCALARS**, along with the resource utilization plots, which are titled **:monitor: machine**.
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## Plots
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The example calls Matplotlib methods to create several sample plots, and TensorBoard methods to plot histograms for layer density.
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They appear in **RESULTS** **>** **PLOTS**.
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They appear in **PLOTS**.
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@ -33,7 +33,7 @@ They appear in **RESULTS** **>** **PLOTS**.
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## Debug Samples
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The example calls Matplotlib methods to log debug sample images. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
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The example calls Matplotlib methods to log debug sample images. They appear in **DEBUG SAMPLES**.
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@ -65,7 +65,7 @@ The TensorFlow Definitions appear in the **TF_DEFINE** subsection.
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## Console
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Text printed to the console for training appears in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training appears in **CONSOLE**.
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@ -22,14 +22,14 @@ The example script does the following:
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## Scalars
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The loss and accuracy metric scalar plots appear in **RESULTS** **>** **SCALARS**, along with the resource utilization plots,
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The loss and accuracy metric scalar plots appear in **SCALARS**, along with the resource utilization plots,
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which are titled **:monitor: machine**.
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## Histograms
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Histograms for layer density appear in **RESULTS** **>** **PLOTS**.
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Histograms for layer density appear in **PLOTS**.
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@ -47,7 +47,7 @@ TensorFlow Definitions appear in **TF_DEFINE**.
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -13,7 +13,7 @@ The example script does the following:
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## Scalars
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The scalars logged in the experiment can be visualized in a plot, which appears in the ClearML web UI, in the **experiment's page > RESULTS > SCALARS**.
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The scalars logged in the experiment can be visualized in a plot, which appears in the ClearML web UI, in the **experiment's page > SCALARS**.
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@ -32,7 +32,7 @@ models and any snapshots created using LightGBM.
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## Console
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All other console output appears in **RESULTS > CONSOLE**.
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All other console output appears in **CONSOLE**.
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@ -20,7 +20,7 @@ which is associated with the `examples` project (in script) or the `Colab notebo
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## Plots
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The scatter plots appear in the **ClearML Web UI**, in **RESULTS** **>** **PLOTS**.
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The scatter plots appear in the **ClearML Web UI**, in **PLOTS**.
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@ -30,7 +30,7 @@ The scatter plots appear in the **ClearML Web UI**, in **RESULTS** **>** **PLOTS
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## Debug Samples
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The images appear in **RESULTS** **>** **DEBUG SAMPLES**. Each debug sample image is associated with a metric.
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The images appear in **DEBUG SAMPLES**. Each debug sample image is associated with a metric.
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@ -25,7 +25,7 @@ The example script's `train` function calls TensorBoardX's `SummaryWriter.add_sc
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ClearML automatically captures the data that is added to the `SummaryWriter` object.
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These scalars can be visualized in plots, which appear in the ClearML [WebApp](../../../webapp/webapp_home.md), in the
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experiment's **RESULTS** **>** **SCALARS** page.
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experiment's **SCALARS** page.
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@ -49,6 +49,6 @@ The model info panel contains the model details, including:
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## Console
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All console output during the script’s execution appears in the experiment’s **RESULTS > CONSOLE** page.
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All console output during the script’s execution appears in the experiment’s **CONSOLE** page.
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@ -6,13 +6,13 @@ The example [audio_classification_UrbanSound8K.ipynb](https://github.com/allegro
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## Scalars
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The accuracy, learning rate, and training loss scalars are automatically logged, along with the resource utilization plots (titled **:monitor: machine**), and appear **RESULTS** **>** **SCALARS**.
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The accuracy, learning rate, and training loss scalars are automatically logged, along with the resource utilization plots (titled **:monitor: machine**), and appear in **SCALARS**.
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## Debug Samples
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The audio samples and spectrogram plots are automatically logged and appear in **RESULTS** **>** **DEBUG SAMPLES**.
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The audio samples and spectrogram plots are automatically logged and appear in **DEBUG SAMPLES**.
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### Audio Samples
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@ -46,6 +46,6 @@ TensorFlow Definitions appear in the **TF_DEFINE** subsection.
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -7,13 +7,13 @@ demonstrates integrating ClearML into a Jupyter Notebook which uses PyTorch and
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## Plots
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ClearML automatically logs the waveform which the example reports by calling a Matplotlib method. These appear in **RESULTS** **>** **PLOTS**.
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ClearML automatically logs the waveform which the example reports by calling a Matplotlib method. These appear in **PLOTS**.
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## Debug Samples
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ClearML automatically logs the audio samples which the example reports by calling TensorBoard methods, and the spectrogram visualizations reported by calling Matplotlib methods. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
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ClearML automatically logs the audio samples which the example reports by calling TensorBoard methods, and the spectrogram visualizations reported by calling Matplotlib methods. They appear in **DEBUG SAMPLES**.
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### Audio Samples
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@ -58,14 +58,14 @@ optimizer = HyperParameterOptimizer(
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### Console
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All console output appears in the optimizer task's **RESULTS > CONSOLE**.
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All console output appears in the optimizer task's **CONSOLE**.
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### Scalars
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Scalar metrics for total accuracy and remaining budget by iteration, and a plot of total accuracy by iteration appear in the
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experiment's **RESULTS** **>** **SCALARS**. Remaining budget indicates the percentage of total iterations for all jobs left before that total is reached.
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experiment's **SCALARS**. Remaining budget indicates the percentage of total iterations for all jobs left before that total is reached.
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ClearML automatically reports the scalars generated by `HyperParameterOptimizer`.
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@ -74,7 +74,7 @@ ClearML automatically reports the scalars generated by `HyperParameterOptimizer`
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### Plots
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The optimization task automatically records and monitors the different trial tasks' configuration and execution details, and
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provides a summary of the optimization results in tabular and parallel coordinate formats. View these plots in the task's **RESULTS** **>**
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provides a summary of the optimization results in tabular and parallel coordinate formats. View these plots in the task's
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**PLOTS**.
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@ -13,13 +13,13 @@ Another example optimizes the hyperparameters for this image classification exam
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## Scalars
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The accuracy, accuracy per class, and training loss scalars are automatically logged, along with the resource utilization plots (titled **:monitor: machine**), and appear **RESULTS** **>** **SCALARS**.
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The accuracy, accuracy per class, and training loss scalars are automatically logged, along with the resource utilization plots (titled **:monitor: machine**), and appear **SCALARS**.
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## Debug Samples
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The image samples are automatically logged and appear in **RESULTS** **>** **DEBUG SAMPLES**.
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The image samples are automatically logged and appear in **DEBUG SAMPLES**.
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@ -45,6 +45,6 @@ TensorFlow Definitions appear in the **TF_DEFINE** subsection.
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -29,7 +29,7 @@ For example, the raw data is read into a Pandas DataFrame named `train_set`, and
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train_set = pd.read_csv(Path(path_to_ShelterAnimal) / 'train.csv')
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Logger.current_logger().report_table(title='ClearMLet - raw',series='pandas DataFrame',iteration=0, table_plot=train_set.head())
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The tables appear in **RESULTS** **>** **PLOTS**.
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The tables appear in **PLOTS**.
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@ -48,6 +48,6 @@ Parameter dictionaries appear in the **General** subsection.
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## Console
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Output to the console appears in **RESULTS** **>** **CONSOLE**.
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Output to the console appears in **CONSOLE**.
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@ -85,7 +85,7 @@ configuration_dict = task.connect(configuration_dict) # enabling configuration
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ClearML tracks and reports each instance of the preprocessing Task.
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The raw data appears as a table in **RESULTS** **>** **PLOTS**.
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The raw data appears as a table in **PLOTS**.
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These images are from one of the two preprocessing Tasks.
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@ -159,7 +159,7 @@ configuration_dict = task.connect(configuration_dict) # enabling configuration
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ClearML tracks and reports the training step with each instance of the newly cloned and executed training Task.
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ClearML automatically logs training loss and learning. They appear in **RESULTS** **>** **SCALARS**.
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ClearML automatically logs training loss and learning. They appear in **SCALARS**.
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The following images show one of the two training Tasks.
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@ -209,7 +209,7 @@ configuration_dict = {
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configuration_dict = task.connect(configuration_dict) # enabling configuration override by clearml
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```
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The logs show the Task ID and accuracy for the best model in **RESULTS** **>** **LOGS**.
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The logs show the Task ID and accuracy for the best model in **CONSOLE**.
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@ -242,7 +242,7 @@ pipe.stop()
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<summary className="cml-expansion-panel-summary">ClearML tracks and reports the pipeline's execution</summary>
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<div className="cml-expansion-panel-content">
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ClearML reports the pipeline with its steps in **RESULTS** **>** **PLOTS**.
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ClearML reports the pipeline with its steps in **PLOTS**.
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@ -8,7 +8,7 @@ to classify text in the `torchtext` [AG_NEWS](https://pytorch.org/text/stable/da
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## Scalars
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Accuracy, learning rate, and training loss appear in **RESULTS** **>** **SCALARS**, along with the resource utilization plots, which are titled **:monitor: machine**.
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Accuracy, learning rate, and training loss appear in **SCALARS**, along with the resource utilization plots, which are titled **:monitor: machine**.
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@ -36,7 +36,7 @@ Parameter dictionaries appear in the **General** subsection.
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -41,7 +41,7 @@ Logger.current_logger().report_scalar(
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```
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These scalars can be visualized in plots, which appear in the [ClearML web UI](../../../webapp/webapp_overview.md), in
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the experiment's page **>** **RESULTS** **>** **SCALARS**.
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the experiment's page **>** **SCALARS**.
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@ -54,7 +54,7 @@ ClearML automatically logs command line options defined with abseil flags. They
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## Console
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Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
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Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
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@ -42,7 +42,7 @@ same title (`loss`), but a different series name (containing the subprocess' `ra
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Task.current_task().get_logger().report_scalar(
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'loss', 'worker {:02d}'.format(dist.get_rank()), value=loss.item(), iteration=i)
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The single scalar plot for loss appears in **RESULTS** **>** **SCALARS**.
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The single scalar plot for loss appears in **SCALARS**.
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@ -73,6 +73,6 @@ Task.current_task().connect(param)
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## Log
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Output to the console, including the text messages printed from the main Task object and each subprocess, appears in **RESULTS** **>** **CONSOLE**.
|
||||
Output to the console, including the text messages printed from the main Task object and each subprocess, appears in **CONSOLE**.
|
||||
|
||||
|
||||
@ -12,7 +12,7 @@ The example does the following:
|
||||
|
||||
## Debug Samples
|
||||
|
||||
The images shown in the example script's `imshow` function appear according to metric in **RESULTS** **>** **DEBUG SAMPLES**.
|
||||
The images shown in the example script's `imshow` function appear according to metric in **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -34,7 +34,7 @@ Logger.current_logger().report_scalar(
|
||||
```
|
||||
|
||||
These scalars can be visualized in plots, which appear in the ClearML [web UI](../../../webapp/webapp_overview.md),
|
||||
in the experiment's page **>** **RESULTS** **>** **SCALARS**.
|
||||
in the experiment's page **>** **SCALARS**.
|
||||
|
||||
|
||||
|
||||
@ -46,7 +46,7 @@ ClearML automatically logs command line options defined with `argparse`. They ap
|
||||
|
||||
## Console
|
||||
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -16,13 +16,13 @@ The example does the following:
|
||||
|
||||
In the example script, the `train` and `test` functions call the TensorBoard `SummaryWriter.add_scalar` method to log loss.
|
||||
These scalars, along with the resource utilization plots, which are titled **:monitor: machine**, appear in the experiment's
|
||||
page in the [ClearML web UI](../../../webapp/webapp_overview.md) under **RESULTS** **>** **SCALARS**.
|
||||
page in the [ClearML web UI](../../../webapp/webapp_overview.md) under **SCALARS**.
|
||||
|
||||
|
||||
|
||||
## Debug Samples
|
||||
|
||||
ClearML automatically tracks images and text output to TensorFlow. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
|
||||
ClearML automatically tracks images and text output to TensorFlow. They appear in **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
|
||||
@ -34,7 +34,7 @@ ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATIO
|
||||
|
||||
## Console
|
||||
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -15,7 +15,7 @@ The example does the following:
|
||||
## Scalars
|
||||
|
||||
The loss and accuracy metric scalar plots, along with the resource utilization plots, which are titled **:monitor: machine**,
|
||||
appear in the experiment's page in the [web UI](../../../webapp/webapp_overview.md), under **RESULTS** **>** **SCALARS**.
|
||||
appear in the experiment's page in the [web UI](../../../webapp/webapp_overview.md), under **SCALARS**.
|
||||
|
||||
|
||||
|
||||
@ -29,7 +29,7 @@ ClearML automatically logs command line options defined with `argparse`. They ap
|
||||
|
||||
## Log
|
||||
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -9,8 +9,7 @@ associated with the `examples` project.
|
||||
|
||||
## Debug Samples
|
||||
|
||||
The debug sample images appear according to metric, in the experiment page in the **ClearML web UI** under **RESULTS**
|
||||
**>** **DEBUG SAMPLES**.
|
||||
The debug sample images appear according to metric, in the experiment page in the **ClearML web UI** under **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -35,7 +35,7 @@ into a script which uses `TensorboardLogger`, all information logged through the
|
||||
|
||||
ClearML automatically captures scalars logged through `TensorboardLogger`.
|
||||
|
||||
View the scalars in the experiment's page in the **ClearML Web UI**, in **RESULTS** **>** **SCALARS**.
|
||||
View the scalars in the experiment's page in the **ClearML Web UI**, in **SCALARS**.
|
||||
|
||||
|
||||
|
||||
@ -55,7 +55,7 @@ To view the model, in the **ARTIFACTS** tab, click the model name (or download i
|
||||
|
||||
## Debug Samples
|
||||
|
||||
ClearML automatically tracks images logged to TensorboardLogger. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
|
||||
ClearML automatically tracks images logged to TensorboardLogger. They appear in **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -142,7 +142,7 @@ When the code runs, the experiment results can be viewed in the [ClearML Web UI]
|
||||
### Scalars
|
||||
|
||||
View the scalars, including training and validation metrics, in the experiment's page in the ClearML Web UI, under
|
||||
**RESULTS** **>** **SCALARS**.
|
||||
**SCALARS**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -12,7 +12,7 @@ The example script does the following:
|
||||
|
||||
## Scalars
|
||||
|
||||
The test loss and validation loss plots appear in the experiment's page in the ClearML web UI under **RESULTS > SCALARS**.
|
||||
The test loss and validation loss plots appear in the experiment's page in the ClearML web UI under **SCALARS**.
|
||||
Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab. All of these
|
||||
plots are automatically captured by ClearML.
|
||||
|
||||
@ -37,7 +37,7 @@ the model’s details and access the model.
|
||||
|
||||
## Console
|
||||
|
||||
All other console output appears in **RESULTS > CONSOLE**.
|
||||
All other console output appears in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -10,7 +10,7 @@ and `matplotlib` to create a scatter diagram. When the script runs, it creates a
|
||||
## Plots
|
||||
|
||||
ClearML automatically logs the scatter plot, which appears in the [experiment's page](../../../webapp/webapp_exp_track_visual.md)
|
||||
in the ClearML web UI, under **RESULTS** **>** **PLOTS**.
|
||||
in the ClearML web UI, under **PLOTS**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -13,6 +13,6 @@ The example does the following:
|
||||
|
||||
## Plots
|
||||
|
||||
The learning curve plots appear in the **ClearML web UI** under **RESULTS** **>** **PLOTS**.
|
||||
The learning curve plots appear in the **ClearML web UI** under **PLOTS**.
|
||||
|
||||
|
||||
@ -14,7 +14,7 @@ The script does the following:
|
||||
## Scalars
|
||||
|
||||
The loss and accuracy metric scalar plots appear in the experiment's page in the **ClearML web UI**, under
|
||||
**RESULTS** **>** **SCALARS**. The also includes resource utilization plots, which are titled **:monitor: machine**.
|
||||
**SCALARS**. The also includes resource utilization plots, which are titled **:monitor: machine**.
|
||||
|
||||
|
||||
|
||||
@ -27,7 +27,7 @@ ClearML automatically logs command line options defined with `argparse`. They ap
|
||||
|
||||
## Console
|
||||
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **RESULTS** **>** **CONSOLE**.
|
||||
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -12,7 +12,7 @@ the `examples` project.
|
||||
## Debug Samples
|
||||
|
||||
ClearML automatically captures the video data that is added to the `SummaryWriter` object, using the `add_video` method.
|
||||
The video appears in the experiment page in the ClearML web UI under **RESULTS > DEBUG SAMPLES**.
|
||||
The video appears in the experiment page in the ClearML web UI under **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -36,14 +36,14 @@ When the script runs, it logs:
|
||||
## Scalars
|
||||
|
||||
ClearML logs the scalars from training each network. They appear in the project's page in the **ClearML web UI**, under
|
||||
**RESULTS** **>** **SCALARS**.
|
||||
**SCALARS**.
|
||||
|
||||
|
||||
|
||||
## Summary of Hyperparameter Optimization
|
||||
|
||||
ClearML automatically logs the parameters of each experiment run in the hyperparameter search. They appear in tabular
|
||||
form in **RESULTS** **>** **PLOTS**.
|
||||
form in **PLOTS**.
|
||||
|
||||
|
||||
|
||||
@ -65,13 +65,13 @@ The model configuration is stored with the model.
|
||||
|
||||
### Hyperparameters
|
||||
|
||||
ClearML automatically logs the TensorFlow Definitions, which appear in **RESULTS** **>** **CONFIGURATION** **>** **HYPER PARAMETERS**.
|
||||
ClearML automatically logs the TensorFlow Definitions, which appear in **CONFIGURATION** **>** **HYPER PARAMETERS**.
|
||||
|
||||
|
||||
|
||||
### Configuration
|
||||
|
||||
The Task configuration appears in **RESULTS** **>** **CONFIGURATION** **>** **General**.
|
||||
The Task configuration appears in **CONFIGURATION** **>** **General**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -16,7 +16,7 @@ The example script does the following:
|
||||
|
||||
## Plots
|
||||
|
||||
In the **ClearML Web UI**, the PR Curve summaries appear in the experiment's page under **RESULTS** **>** **PLOTS**.
|
||||
In the **ClearML Web UI**, the PR Curve summaries appear in the experiment's page under **PLOTS**.
|
||||
|
||||
* Blue PR curves
|
||||
|
||||
@ -33,6 +33,6 @@ ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATIO
|
||||
|
||||
## Console
|
||||
|
||||
All other console output appears in **RESULTS** **>** **CONSOLE**.
|
||||
All other console output appears in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
@ -11,20 +11,20 @@ project.
|
||||
|
||||
## Scalars
|
||||
|
||||
The `tf.summary.scalar` output appears in the ClearML web UI, in the experiment's **RESULTS** **>**
|
||||
The `tf.summary.scalar` output appears in the ClearML web UI, in the experiment's
|
||||
**SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab.
|
||||
|
||||
|
||||
|
||||
## Plots
|
||||
|
||||
The `tf.summary.histogram` output appears in **RESULTS** **>** **PLOTS**.
|
||||
The `tf.summary.histogram` output appears in **PLOTS**.
|
||||
|
||||
|
||||
|
||||
## Debug Samples
|
||||
|
||||
ClearML automatically tracks images and text output to TensorFlow. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
|
||||
ClearML automatically tracks images and text output to TensorFlow. They appear in **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -10,8 +10,8 @@ When the script runs, it creates an experiment named `Tensorflow v2 mnist with s
|
||||
|
||||
## Scalars
|
||||
|
||||
The loss and accuracy metric scalar plots appear in the experiment's page in the **ClearML web UI** under **RESULTS**
|
||||
**>** **SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab.
|
||||
The loss and accuracy metric scalar plots appear in the experiment's page in the **ClearML web UI** under
|
||||
**SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab.
|
||||
|
||||
|
||||
|
||||
@ -24,7 +24,7 @@ ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATIO
|
||||
|
||||
## Console
|
||||
|
||||
All console output appears in **RESULTS** **>** **CONSOLE**.
|
||||
All console output appears in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -11,7 +11,7 @@ the `examples` project.
|
||||
|
||||
## Scalars
|
||||
ClearML automatically captures scalars logged with XGBoost, which can be visualized in plots in the
|
||||
ClearML WebApp, in the experiment's **RESULTS > SCALARS** page.
|
||||
ClearML WebApp, in the experiment's **SCALARS** page.
|
||||
|
||||
|
||||
|
||||
@ -29,6 +29,6 @@ To view the model details, click the model name in the **ARTIFACTS** page, which
|
||||
|
||||
## Console
|
||||
|
||||
All console output during the script’s execution appears in the experiment’s **RESULTS > CONSOLE** page.
|
||||
All console output during the script’s execution appears in the experiment’s **CONSOLE** page.
|
||||
|
||||
|
||||
@ -15,14 +15,14 @@ classification dataset using XGBoost
|
||||
|
||||
## Plots
|
||||
|
||||
The feature importance plot and tree plot appear in the project's page in the **ClearML web UI**, under **RESULTS** **>**
|
||||
The feature importance plot and tree plot appear in the project's page in the **ClearML web UI**, under
|
||||
**PLOTS**.
|
||||
|
||||
|
||||
|
||||
## Console
|
||||
|
||||
All other console output appear in **RESULTS** **>** **CONSOLE**.
|
||||
All other console output appear in **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -7,7 +7,7 @@ example demonstrates reporting a series as a surface plot and as a 3D scatter pl
|
||||
|
||||
When the script runs, it creates an experiment named `3D plot reporting`, which is associated with the `examples` project.
|
||||
|
||||
ClearML reports these plots in the **ClearML Web UI** **>** experiment page **>** **RESULTS** tab **>** **PLOTS** sub-tab.
|
||||
ClearML reports these plots in the **ClearML Web UI** **>** experiment page **>** **PLOTS** tab.
|
||||
|
||||
## Surface Plot
|
||||
|
||||
@ -27,7 +27,7 @@ Logger.current_logger().report_surface(
|
||||
zaxis="title Z",
|
||||
)
|
||||
```
|
||||
Visualize the reported surface plot in **RESULTS** **>** **PLOTS**.
|
||||
Visualize the reported surface plot in **PLOTS**.
|
||||
|
||||
|
||||
|
||||
@ -49,5 +49,5 @@ Logger.current_logger().report_scatter3d(
|
||||
)
|
||||
```
|
||||
|
||||
Visualize the reported 3D scatter plot in **RESULTS** **>** **PLOTS**.
|
||||
Visualize the reported 3D scatter plot in **PLOTS**.
|
||||
|
||||
|
||||
@ -18,7 +18,7 @@ In the ``clearml`` GitHub repository, this example includes a clickable icon to
|
||||
## Scalars
|
||||
|
||||
To reports scalars, call the [Logger.report_scalar](../../references/sdk/logger.md#report_scalar)
|
||||
method. The scalar plots appear in the **web UI** in **RESULTS** **>** **SCALARS**.
|
||||
method. The scalar plots appear in the **web UI** in **SCALARS**.
|
||||
|
||||
```python
|
||||
# report two scalar series on two different graphs
|
||||
@ -40,7 +40,7 @@ for i in range(10):
|
||||
|
||||
## Plots
|
||||
|
||||
Plots appear in **RESULTS** **>** **PLOTS**.
|
||||
Plots appear in **PLOTS**.
|
||||
|
||||
### 2D Plots
|
||||
|
||||
@ -171,7 +171,7 @@ logger.report_histogram(
|
||||
## Media
|
||||
|
||||
Report audio, HTML, image, and video by calling the [Logger.report_media](../../references/sdk/logger.md#report_media)
|
||||
method using the `local_path` parameter. They appear in **RESULTS** **>** **DEBUG SAMPLES**.
|
||||
method using the `local_path` parameter. They appear in **DEBUG SAMPLES**.
|
||||
|
||||
The media for these examples is downloaded using the [StorageManager.get_local_copy](../../references/sdk/storage.md#storagemanagerget_local_copy)
|
||||
method.
|
||||
|
||||
@ -290,10 +290,9 @@ python pytorch_mnist_tutorial.py
|
||||
1. In the **ARTIFACTS** tab, **DATA AUDIT** section, click **Test_Loss_Correct**. The registered Pandas DataFrame appears,
|
||||
including the file path, size, hash, metadata, and a preview.
|
||||
1. In the **OTHER** section, click **Loss**. The uploaded numpy array appears, including its related information.
|
||||
1. Click the **RESULTS** tab.
|
||||
1. Click the **CONSOLE** sub-tab, and see the debugging message showing the Pandas DataFrame sample.
|
||||
1. Click the **SCALARS** sub-tab, and see the scalar plots for epoch logging loss.
|
||||
1. Click the **PLOTS** sub-tab, and see the confusion matrix and histogram.
|
||||
1. Click the **CONSOLE** tab, and see the debugging message showing the Pandas DataFrame sample.
|
||||
1. Click the **SCALARS** tab, and see the scalar plots for epoch logging loss.
|
||||
1. Click the **PLOTS** tab, and see the confusion matrix and histogram.
|
||||
|
||||
## Next Steps
|
||||
|
||||
|
||||
@ -6,8 +6,8 @@ The [html_reporting.py](https://github.com/allegroai/clearml/blob/master/example
|
||||
demonstrates reporting local HTML files and HTML by URL, using the [Logger.report_media](../../references/sdk/logger.md#report_media)
|
||||
method.
|
||||
|
||||
ClearML reports these HTML debug samples in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>**
|
||||
**DEBUG SAMPLES** sub-tab.
|
||||
ClearML reports these HTML debug samples in the **ClearML Web UI** **>** experiment details **>**
|
||||
**DEBUG SAMPLES** tab.
|
||||
|
||||
When the script runs, it creates an experiment named `html samples reporting`, which is associated with the `examples` project.
|
||||
|
||||
|
||||
@ -48,8 +48,8 @@ Logger.current_logger().report_image(
|
||||
)
|
||||
```
|
||||
|
||||
ClearML reports these images as debug samples in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab
|
||||
**>** **DEBUG SAMPLES** sub-tab.
|
||||
ClearML reports these images as debug samples in the **ClearML Web UI** **>** experiment details **>**
|
||||
**DEBUG SAMPLES** tab.
|
||||
|
||||
|
||||
|
||||
|
||||
@ -8,7 +8,7 @@ example demonstrates using ClearML to log plots and images generated by Matplotl
|
||||
## Plots
|
||||
|
||||
The Matplotlib and Seaborn plots that are reported using the [Logger.report_matplotlib_figure](../../references/sdk/logger.md#report_matplotlib_figure)
|
||||
method appear in the experiment’s **RESULTS** **>** **PLOTS**.
|
||||
method appear in the experiment’s **PLOTS**.
|
||||
|
||||
|
||||
|
||||
@ -17,6 +17,6 @@ method appear in the experiment’s **RESULTS** **>** **PLOTS**.
|
||||
## Debug Samples
|
||||
|
||||
Matplotlib figures can be logged as images by using the [Logger.report_matplotlib_figure](../../references/sdk/logger.md#report_matplotlib_figure)
|
||||
method, and passing `report_image=True`. The images are stored in the experiment’s **RESULTS > DEBUG SAMPLES**.
|
||||
method, and passing `report_image=True`. The images are stored in the experiment’s **DEBUG SAMPLES**.
|
||||
|
||||
|
||||
@ -13,8 +13,8 @@ ClearML uploads media to the bucket specified in the ClearML configuration file
|
||||
(storage for [artifacts](../../clearml_sdk/task_sdk.md#setting-upload-destination) is different). Set credentials for storage in the ClearML
|
||||
[configuration file](../../configs/clearml_conf.md).
|
||||
|
||||
ClearML reports media in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>** **DEBUG SAMPLES**
|
||||
sub-tab.
|
||||
ClearML reports media in the **ClearML Web UI** **>** experiment details **>** **DEBUG SAMPLES**
|
||||
tab.
|
||||
|
||||
When the script runs, it creates an experiment named `audio and video reporting`, which is associated with the `examples`
|
||||
project.
|
||||
@ -38,7 +38,7 @@ Logger.current_logger().report_media(
|
||||
)
|
||||
```
|
||||
|
||||
The reported audio can be viewed in the **DEBUG SAMPLES** sub-tab. Double click a thumbnail, and the audio player opens.
|
||||
The reported audio can be viewed in the **DEBUG SAMPLES** tab. Double click a thumbnail, and the audio player opens.
|
||||
|
||||
|
||||
|
||||
@ -55,6 +55,6 @@ Logger.current_logger().report_media(
|
||||
)
|
||||
```
|
||||
|
||||
The reported video can be viewed in the **DEBUG SAMPLES** sub-tab. Double click a thumbnail, and the video player opens.
|
||||
The reported video can be viewed in the **DEBUG SAMPLES** tab. Double click a thumbnail, and the video player opens.
|
||||
|
||||
|
||||
|
||||
@ -4,8 +4,8 @@ title: Tables Reporting (Pandas and CSV Files)
|
||||
|
||||
The [pandas_reporting.py](https://github.com/allegroai/clearml/blob/master/examples/reporting/pandas_reporting.py) example demonstrates reporting tabular data from Pandas DataFrames and CSV files as tables.
|
||||
|
||||
ClearML reports these tables in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>** **PLOTS**
|
||||
sub-tab.
|
||||
ClearML reports these tables in the **ClearML Web UI** **>** experiment details **>** **PLOTS**
|
||||
tab.
|
||||
|
||||
When the script runs, it creates an experiment named `table reporting`, which is associated with the `examples` project.
|
||||
|
||||
|
||||
@ -33,7 +33,7 @@ task.get_logger().report_plotly(
|
||||
|
||||
When the script runs, it creates an experiment named `plotly reporting`, which is associated with the examples project.
|
||||
|
||||
ClearML reports Plotly plots in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>** **PLOTS**
|
||||
sub-tab.
|
||||
ClearML reports Plotly plots in the **ClearML Web UI** **>** experiment details **>** **PLOTS**
|
||||
tab.
|
||||
|
||||
|
||||
@ -3,8 +3,8 @@ title: Scalars Reporting
|
||||
---
|
||||
|
||||
The [scalar_reporting.py](https://github.com/allegroai/clearml/blob/master/examples/reporting/scalar_reporting.py) script
|
||||
demonstrates explicit scalar reporting. ClearML reports scalars in the **ClearML Web UI** **>** experiment details **>**
|
||||
**RESULTS** tab **>** **SCALARS** sub-tab.
|
||||
demonstrates explicit scalar reporting. ClearML reports scalars in the **ClearML Web UI** **>** experiment details
|
||||
**>** **SCALARS** tab.
|
||||
|
||||
When the script runs, it creates an experiment named `scalar reporting`, which is associated with the `examples` project.
|
||||
|
||||
|
||||
@ -8,7 +8,7 @@ example demonstrates reporting series data in the following 2D formats:
|
||||
* [Confusion matrices](#confusion-matrices)
|
||||
* [Scatter plots](#2d-scatter-plots)
|
||||
|
||||
ClearML reports these tables in the **ClearML Web UI**, experiment details **>** **RESULTS** tab **>** **PLOTS** sub-tab.
|
||||
ClearML reports these tables in the **ClearML Web UI**, experiment details **>** **PLOTS** tab.
|
||||
|
||||
When the script runs, it creates an experiment named `2D plots reporting`, which is associated with the `examples` project.
|
||||
|
||||
|
||||
@ -6,7 +6,7 @@ The [text_reporting.py](https://github.com/allegroai/clearml/blob/master/example
|
||||
demonstrates reporting explicit text, by calling the [Logger.report_text](../../references/sdk/logger.md#report_text)
|
||||
method.
|
||||
|
||||
ClearML reports these tables in the **ClearML Web UI**, experiment details, **RESULTS** tab, **CONSOLE** sub-tab.
|
||||
ClearML reports these tables in the **ClearML Web UI**, experiment details, **CONSOLE** tab.
|
||||
|
||||
When the script runs, it creates an experiment named `text reporting`, which is associated with the `examples` project.
|
||||
|
||||
|
||||
@ -166,6 +166,6 @@ in [services mode](../../clearml_agent.md#services-mode) for such service tasks)
|
||||
|
||||
### Console
|
||||
|
||||
All other console output appears in the experiment’s **RESULTS > CONSOLE**.
|
||||
All other console output appears in the experiment’s **CONSOLE**.
|
||||
|
||||
|
||||
@ -60,6 +60,6 @@ The task can be reused. Clone the task, edit its parameters, and enqueue the tas
|
||||
|
||||
|
||||
## Console
|
||||
All console output appears in the experiment’s **RESULTS > CONSOLE**.
|
||||
All console output appears in the experiment’s **CONSOLE**.
|
||||
|
||||
|
||||
|
||||
@ -86,7 +86,7 @@ execution (you’ll typically want to use a ClearML Agent running in [services m
|
||||
for such service tasks).
|
||||
|
||||
## Console
|
||||
All console output appears in the experiment’s **RESULTS > CONSOLE** page.
|
||||
All console output appears in the experiment’s **CONSOLE** page.
|
||||
|
||||
## Additional Information about slack_alerts.py
|
||||
|
||||
|
||||
@ -21,7 +21,7 @@ title: Version 1.5
|
||||
**Bug Fixes**
|
||||
* Fix UI experiment debug samples disappearing after refresh [ClearML Server GitHub issue #136](https://github.com/allegroai/clearml-server/issues/136)
|
||||
* Fix deleting tasks sometimes raises errors [ClearML GitHub issue #632](https://github.com/allegroai/clearml/issues/632)
|
||||
* Fix Only partial task log shown when running on ES with multiple shards
|
||||
* Fix only partial task log shown when running on ES with multiple shards
|
||||
* Fix move task to trash is not thread-safe
|
||||
* Fix UI Project overview metric snapshot not showing
|
||||
* Fix no progress indicator when performing off-screen selection in UI experiments table
|
||||
|
||||
@ -259,7 +259,7 @@ is downloadable. To view the end of the log, click **Jump to end**.
|
||||
|
||||
### Scalars
|
||||
|
||||
All scalars that ClearML automatically logs, as well as those explicitly reported in code, appear in **RESULTS** **>**
|
||||
All scalars that ClearML automatically logs, as well as those explicitly reported in code, appear in
|
||||
**SCALARS**. Scalar values are presented as time series line chart. To see the series for a metric in high resolution,
|
||||
view it in full screen mode by hovering over the graph and clicking <img src="/docs/latest/icons/ico-maximize.svg" alt="Maximize plot icon" className="icon size-sm space-sm" />.
|
||||
|
||||
@ -307,7 +307,7 @@ are on the left side of the window. The tools include:
|
||||
See additional [plot controls](#plot-controls) below.
|
||||
|
||||
### Plots
|
||||
Non-time-series plots appear in **RESULTS** **>** **PLOTS**. These include data reported by libraries, visualization
|
||||
Non-time-series plots appear in **PLOTS**. These include data reported by libraries, visualization
|
||||
tools, and ClearML explicit reporting. These may include 2D and 3D plots, tables (Pandas and CSV files), and Plotly plots.
|
||||
Individual plots can be shown / hidden or filtered by title.
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user